Software

Torch

"Torch is a deep learning framework with wide support for machine learning algorithms. It's open-source, simple to use, and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C / CUDA implementation. Torch offers popular neural network and optimization libraries that are easy to use, yet provide maximum flexibility to build complex neural network topologies. It also runs up to 70% faster on the latest NVIDIA Pascal™ GPUs, so you can now train networks in hours, instead of days."

TensorFlow

"TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code."

Quote from TensorFlow Github documentation

Software Refresh - February 2017

OSC is refreshing the software stack for Oakley and Ruby on February 22, 2017 (during the scheduled downtime). During the software refresh, some default versions are updated to be more up-to-date and some older versions are removed. Information about the old and new default versions, as well as all available versions of each software package will be included on the corresponding OSC software webpage. See https://www.osc.edu/supercomputing/software-list.

Darshan

Darshan is a lightweight "scalable HPC I/O characterization tool".  It is intended to profile I/O by emitting log files to a consistent log location for systems administrators, and also provides scripts to create summary PDFs to characterize I/O in MPI-based programs.

Availability and Restrictions

Versions

The following versions of Darshan are available on OSC clusters:

Spark

Apache Spark is an open source cluster-computing framework originally developed in the AMPLab at University of California, Berkeley but was later donated to the Apache Software Foundation where it remains today. In contrast to Hadoop's disk-based analytics paradigm, Spark has multi-stage in-memory analytics. Spark can run programs up-to 100x faster than Hadoop’s MapReduce in memory or 10x faster on disk. Spark support applications written in python, java, scala and R

WARP3D

From WARP3D's webpage:

WARP3D is under continuing development as a research code for the solution of large-scale, 3-Dsolid models subjected to static and dynamic loads. The capabilities of the code focus on 
fatigue & fracture analyses primarily in metals. WARP3D runs on laptops-to-supercomputers and can analyze models with several million nodes and elements. 

Availability and Restrictions

Versions

The following versions of WARP3D are available on OSC clusters:

R and Rstudio

R is a language and environment for statistical computing and graphics. It is an integrated suite of software facilities for data manipulation, calculation, and graphical display. It includes

  • an effective data handling and storage facility,
  • a suite of operators for calculations on arrays, in particular matrices,
  • a large, coherent, integrated collection of intermediate tools for data analysis,
  • graphical facilities for data analysis and display either on-screen or on hardcopy, and
  • a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input, and output facilities

More information can be found here.

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